Unveiling spatial and temporal heterogeneity of a tropical forest canopy using high-resolution NIRv, FCVI, and NIRvrad from UAS observations

Merrick, Trina; Pau, Stephanie; Detto, Matteo; Broadbent, Eben N.; Bohlman, Stephanie A.; Still, Christopher J.; Almeyda Zambrano, Angelica M.

doi:https://doi.org/10.5194/bg-18-6077-2021

Articles | Volume 18, issue 22

https://doi.org/10.5194/bg-18-6077-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-18-6077-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 22

Research article

|

25 Nov 2021

Research article |

| 25 Nov 2021

Unveiling spatial and temporal heterogeneity of a tropical forest canopy using high-resolution NIRv, FCVI, and NIRvrad from UAS observations

Trina Merrick, Stephanie Pau, Matteo Detto, Eben N. Broadbent, Stephanie A. Bohlman, Christopher J. Still, and Angelica M. Almeyda Zambrano

Data sets

Barro Colorado Data Trina Merrick and Eben Broadbent http://www.gatoreye.org

Short summary

Remote sensing measurements of forest structure promise to improve monitoring of tropical forest health. We investigated drone-based vegetation measurements' abilities to capture different structural and functional elements of a tropical forest. We found that emerging vegetation indices captured greater variability than traditional indices and one new index trends with daily change in carbon flux. These new tools can help improve understanding of tropical forest structure and function.